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Order Choice and Information in Limit Order Markets

Author

Listed:
  • Ioanid Rosu

    (GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique)

Abstract

Based on the December 2010 conference on market microstructure, organized with the help of the Institut Louis Bachelier, this guide brings together the leading thinkers to discuss this important field of modern finance. It provides readers with vital insight on the origin of the well-known anomalous "stylized facts" in financial prices series, namely heavy tails, volatility, and clustering, and illustrates their impact on the organization of markets, execution costs, price impact, organization liquidity in electronic markets, and other issues raised by high-frequency trading. World-class contributors cover topics including analysis of high-frequency data, statistics of high-frequency data, market impact, and optimal trading. This is a must-have guide for practitioners and academics in quantitative finance.

Suggested Citation

  • Ioanid Rosu, 2012. "Order Choice and Information in Limit Order Markets," Post-Print hal-00712067, HAL.
    • Handle: RePEc:hal:journl:hal-00712067
    as

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    Citations

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    Cited by:

    1. Chiarella, Carl & He, Xue-Zhong & Wei, Lijian, 2015. "Learning, information processing and order submission in limit order markets," Journal of Economic Dynamics and Control, Elsevier, vol. 61(C), pages 245-268.
    2. Roberto Dieci & Xue-Zhong He, 2018. "Heterogeneous Agent Models in Finance," Research Paper Series 389, Quantitative Finance Research Centre, University of Technology, Sydney.
    3. Arifovic, Jasmina & He, Xue-zhong & Wei, Lijian, 2022. "Machine learning and speed in high-frequency trading," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    4. Lijian Wei & Xiong Xiong & Wei Zhang & Xue-Zhong He & Yongjie Zhang, 2017. "The effect of genetic algorithm learning with a classifier system in limit order markets," Published Paper Series 2017-3, Finance Discipline Group, UTS Business School, University of Technology, Sydney.

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